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Proof of concept demonstration of optimal composite MRI endpoints for clinical trials
Steven D Edland1, M Colin Ard2, Jaiashre Sridhar3
1Division of Biostatistics, Department of Family Medicine & Public Health, University of California San Diego, La Jolla, CA, USA; Department of Neurosciences, University of California San Diego, La Jolla, CA, USA.
Background:
Atrophy measures derived from structural MRI are promising outcome measures for early phase clinical trials, especially for rare diseases such as primary progressive aphasia (PPA), where the small available subject pool limits our ability to perform meaningfully powered trials with traditional cognitive and functional outcome measures.
Methods:
We investigated a composite atrophy index in 26 PPA participants with longitudinal MRIs separated by two years. Rogalski et al. [Neurology 2014;83:1184-1191] previously demonstrated that atrophy of the left perisylvian temporal cortex (PSTC) is a highly sensitive measure of disease progression in this population and a promising endpoint for clinical trials. Using methods described by Ard et al. [Pharmaceutical Statistics 2015;14:418-426], we constructed a composite atrophy index composed of a weighted sum of volumetric measures of 10 regions of interest within the left perisylvian cortex using weights that maximize signal-to-noise and minimize sample size required of trials using the resulting score. Sample size required to detect a fixed percentage slowing in atrophy in a two-year clinical trial with equal allocation of subjects across arms and 90% power was calculated for the PSTC and optimal composite surrogate biomarker endpoints.
Results:
The optimal composite endpoint required 38% fewer subjects to detect the same percent slowing in atrophy than required by the left PSTC endpoint.
Conclusions:
Optimal composites can increase the power of clinical trials and increase the probability that smaller trials are informative, an observation especially relevant for PPA, but also for related neurodegenerative disorders including Alzheimer's disease.
Insights
A new composite atrophy index significantly reduces the number of participants needed for clinical trials in primary progressive aphasia (PPA). This approach enhances trial power and informativeness, particularly for rare neurodegenerative diseases.
Area of Science:
- Neuroimaging
- Biostatistics
- Clinical Trials
Background:
- Structural MRI-derived atrophy measures show promise for early-phase clinical trials.
- Primary progressive aphasia (PPA) presents challenges for traditional outcome measures due to small patient populations.
- Atrophy of the left perisylvian temporal cortex (PSTC) is a sensitive indicator of PPA progression.
Purpose of the Study:
- To investigate a composite atrophy index as a more efficient outcome measure for PPA clinical trials.
- To compare the sample size requirements of a composite index versus the PSTC endpoint.
- To enhance the power and informativeness of clinical trials for rare neurodegenerative diseases.
Main Methods:
- A composite atrophy index was constructed using volumetric MRI data from 26 PPA participants over two years.
- Weights were optimized to maximize signal-to-noise ratio and minimize sample size.
- Sample size calculations were performed for a two-year clinical trial with 90% power.
Main Results:
- The optimal composite endpoint required 38% fewer subjects than the left PSTC endpoint.
- This composite index demonstrated greater efficiency in detecting atrophy progression.
Conclusions:
- Composite atrophy indices can significantly increase the power of clinical trials.
- These optimized endpoints improve the probability of smaller trials yielding informative results.
- This approach is highly relevant for PPA and other neurodegenerative disorders like Alzheimer's disease.
